Shopping malls face major challenges: changing customer needs, high investment backlogs, unsuitable tenant mixes, strong online competition, and outdated business models are forcing them to take urgent action. Shopping centers will only have a bright future if they no longer remain purely consumer temples. However, there is no blueprint for optimizing and revitalizing shopping malls. That is why the data obtained from retail analytics is so important, enabling managers to make the perfect decisions for their specific locations.
Challenges for shopping malls
Shopping malls are constantly changing. This is because the tenant market is also subject to constant change. For example, the preferred retail space is changing. Some retailers are focusing on downsizing, while others are aiming to expand. In addition, there are new retail concepts with new requirements for sales space. Customer consumption habits are also changing. A shopping mall that does not respond to changes, or does so only slowly, loses its appeal.
Optimizing and revitalizing shopping malls involves more than just the external architecture and technical infrastructure. It also includes changing floor plans, integrating new stores, expanding the product range, creating innovative offerings, improving multifunctionality, and investing in digitalization. There are hundreds of options and levers for optimization and revitalization.
The size and structure of each shopping center naturally influences the individual implementation of the respective options. The focus should not only be on extending the length of stay. The quality of the stay and short distances are also important. This is particularly relevant for smaller shopping malls. Shoppers no longer just want to shop, they also want a high-quality stay, exciting experiences, and plenty of inspiration.
Those responsible must therefore analyze, optimize, or revitalize each location individually. It is not enough to transfer a functioning concept from one location to another. This is because locations differ greatly in terms of local conditions. Professional retail analytics is the basis for forward-looking decisions and successful center management.
Retail analytics for data-driven decisions
The collection and compilation of data from shopping centers is nothing new. However, shopping malls still have some catching up to do when it comes to analyzing visitor flows. This is because manually recording visitors and conducting manual customer surveys only ever provides an inaccurate snapshot. For example, they do not allow any conclusions to be drawn about how the layout of the shopping center can be optimized. Manual data is also useless for grouping individual stores. It is also of limited use when it comes to leasing vacant space or restructuring a shopping center in general.
Retail Analytics enables the measurement of visitor frequency during the entire opening hours. With Retail Analytics, managers not only receive information about the total number of visitors to shopping malls. They can also use it to record visitor frequency for individual floors, areas, and stores. This insight enables them to optimize the tenant mix and marketing measures.
Retail analytics is therefore the right tool for analyzing low- and high-traffic areas and routes in shopping malls. Blind spots and dead ends in particular have a negative impact on visitor flow. Architecturally, they are often unavoidable and predetermined. In addition, vacant spaces damage the image of a shopping center. That is why managers do a lot to keep vacancy rates low. With data from retail analytics, prospective tenants can be provided with relevant key figures to help them make their decision.
Since shopping center customers prefer to move horizontally rather than vertically, increasing visitor traffic to upper floors is an ongoing challenge. In addition to adequate infrastructure with escalators and elevators and an open design of access areas, there are other measures that can be taken to increase the attractiveness of each floor. Retail analytics is the right tool for analyzing weak points and making each floor attractive.
Visitors to shopping centers come in all ages, genders, and purchasing behaviors. Retail analytics provides insight into the demographic structure of visitors. With this knowledge, marketing measures can be tailored to specific target groups. It is also possible to automatically and systematically record the license plate numbers of vehicles in the shopping center's parking lot. This allows the catchment area of visitors to be determined, which forms the basis for regional advertising measures.
Optimization and revitalization of shopping malls
Retail analytics helps shopping malls uncover previously neglected data and use it to their advantage. This provides managers with the key figures they need to manage shopping malls in a data-driven way. It also makes it easier for them to identify untapped potential and measure the success of individual development steps. At Crosscan, we are happy to provide you with comprehensive advice on the many possible applications of retail analytics.
Are you ready for the adventure of digital transformation and retail analytics?
Let us turn your vision into reality. Contact us today to get your brand started on the path to data-driven management of your visitor areas.
Crosscan Data Insights Blog
Check out our other blog articles to learn how data-driven insights are transforming brick-and-mortar retail and helping to analyze visitor areas.